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Machine Learning personalization for dynamic digital properties -…
Liftigniter has raised $6.4M across 1 funding round.
Key people at Liftigniter.
Liftigniter was founded in 2013 by Michael Murray (Founder) and Indraneel Mukherjee (Founder).
Liftigniter has raised $6.4M in total across 1 funding round.
LiftIgniter uses cutting edge data science to help publishers and retailers optimize their websites and mobile apps in real-time. Machine learning personalization puts the perfect piece of "content" (video, article, item to buy) in front the user at the exact moment when they are most likely to engage or convert - no tags or manual work required.
The machine learns and updates itself so that's it's always perfectly in sync with your users and your "content." We average 50% improvements in CTR, engagement and conversation - with only a day's work on your part. Imagine creating a truly dynamic, real-time digital property that enables the perfect experience for that user impression at that moment in time. That is LiftIgniter!
Our team of PhDs has direct experience building state-of-the-art personalization systems at the petabyte scale for some of the largest companies on the planet. Unless you plan on hiring your own team with deep experience (not likely since very few people with that experience exist), you should contact us to talk about how we can supercharge your digital experiences.
Liftigniter was founded in 2013 by Michael Murray (Founder) and Indraneel Mukherjee (Founder).
Liftigniter has raised $6.4M in total across 1 funding round.
Liftigniter's investors include Ryan Floyd, Bruce Falck, Tom Chavez, NTT DOCOMO Ventures, Revel Partners, Rincon Venture Partners.
Key people at Liftigniter.
LiftIgniter is an AI-powered machine learning personalization platform designed to deliver real-time, dynamic content recommendations across digital properties. It helps businesses—ranging from e-commerce and media to publishing—enhance user engagement, increase conversions, and optimize content delivery by analyzing user behavior and preferences continuously. The platform is scalable, customizable, and integrates easily with existing systems, enabling companies to tailor user experiences without building new infrastructure[1][2][5].
Founded in 2014, LiftIgniter serves digital publishers, e-commerce businesses, and media companies by solving the problem of generic, non-personalized content that fails to engage users effectively. Its machine learning engine predicts user needs and preferences to provide relevant content at the right time, driving higher satisfaction and business outcomes. The company has demonstrated strong growth momentum, processing billions of page views monthly and raising over $8 million in funding from notable investors like Khosla Ventures and Storm Ventures[2][3][4].
LiftIgniter was founded in 2014 by Indraneel Mukherjee and Adam Spector with the mission to create intelligent, dynamic user experiences through real-time personalization. The founders identified a gap in the market where many digital platforms struggled to deliver personalized content effectively, which led to decreased user engagement and conversion rates. Early traction came from demonstrating measurable success within 30 days of deployment, a key selling point that helped LiftIgniter gain adoption among digital businesses seeking quick returns on personalization investments[2][3][4].
LiftIgniter rides the growing trend of AI-driven personalization, which has become critical as users increasingly expect tailored digital experiences similar to those on platforms like Facebook and Google. The timing is favorable due to the explosion of digital content and the competitive need for businesses to differentiate through user experience. Market forces such as rising e-commerce demand, digital media consumption, and advances in machine learning algorithms work in LiftIgniter’s favor. By providing a plug-and-play personalization layer, LiftIgniter influences the broader ecosystem by enabling companies of all sizes to adopt sophisticated AI personalization without heavy technical overhead[1][4].
Looking ahead, LiftIgniter is well-positioned to expand its influence as personalization becomes a baseline expectation across digital platforms. Trends such as increased data privacy regulation, demand for real-time AI insights, and multi-channel personalization will shape its evolution. The company’s focus on rapid deployment and measurable ROI will continue to attract businesses seeking immediate impact. As competition intensifies, LiftIgniter’s ability to maintain customization flexibility and privacy-conscious approaches will be key to sustaining growth and relevance in the personalization technology market[4][5].
In summary, LiftIgniter exemplifies the shift toward intelligent, machine learning-driven personalization that transforms user engagement and business outcomes in the digital age.
Liftigniter has raised $6.4M across 1 funding round. Most recently, it raised $6.4M Series A in August 2017.
| Date | Round | Lead Investors | Other Investors |
|---|---|---|---|
| Aug 17, 2017 | $6.4M Series A | Ryan Floyd | Bruce Falck, Tom Chavez, NTT DOCOMO Ventures, Revel Partners, Rincon Venture Partners |
